Title :
Conceptual summarization using ontologies and nearest neighborhood clustering
Author :
Gavagsaz, Elahe ; Naghibzadeh, Mahmoud ; Jalali, Mehrdad
Author_Institution :
Dept. of Software Eng., Islamic Azad Univ., Mashhad, Iran
Abstract :
Conceptual summarization aims to provide a database which comprises an abstraction of the entire document content. To effectively provide conceptual summarization, we have presented an approach that is used for conceptual querying. The approach is based on utilizing an ontology for similarity measure between concepts and the nearest neighborhood clustering algorithm for concepts clustering. The results show an improvement in the runtime and tolerant as regards noise.
Keywords :
document handling; ontologies (artificial intelligence); pattern clustering; query processing; conceptual querying; conceptual summarization; document content; nearest neighborhood clustering; ontology; similarity measure; Classification algorithms; Clustering algorithms; Clustering methods; Noise; Ontologies; Semantics; Software algorithms; conceptual summarization; nearest neighborhood clustering; ontology;
Conference_Titel :
Semantic Technology and Information Retrieval (STAIR), 2011 International Conference on
Conference_Location :
Putrajaya
Print_ISBN :
978-1-61284-354-4
Electronic_ISBN :
978-1-61284-353-7
DOI :
10.1109/STAIR.2011.5995756
